Chimpanzee optimization algorithm incorporating Cat mapping and Gauss mutation and its application
A modified Chimpanzee Algorithm(CGChOA)is proposed to address the issues of uneven initial population distri-bution,poor individual adaptability,and susceptibility to local optima that arise during the optimization process of the standard Chimpanzee optimization algorithm.Firstly,using chaotic Cat mapping to generate the initial position of the chimpanzee population to enrich population diversity;Secondly,a convergence factor based on the cosine variation law is introduced to balance the global exploration and local development capabilities of the algorithm;Finally,Gaussian mutation is performed on the individuals of chim-panzees at the best search location to avoid the algorithm falling into local optima.The superiority of our algorithm was verified through comparative experiments of 10 benchmark test functions and 2 engineering application problems.
Chimpanzee optimization algorithmCat mappingconvergence factorGaussian variationsurvival of the fittest
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